After you’ve built the business case for how to solve your company’s big data analytics problem, you may be left wondering if proposing data analytics software will make your role obsolete.
Never fear, what you propose will make you an analytics hero and an invaluable part of your company.

SAN FRANCISCO — There was nothing subtle about Oracle CTO Larry Ellison’s message during his mid-week keynote at OpenWorld, the company's annual user conference here: He had nothing nice to say about Amazon Web Services (AWS).

The data analytics marketplace can at times look like an obstacle course.
With so many vendors claiming to have the right tool for the right problem — which is nearly every problem — it can get noisy and confusing.

It wasn't too long ago when business users struggled to answer simple questions like, “Who are my top 10 customers? Who are my top five suppliers? Are people opening and reading our email campaigns?”
As recently as the early 2000s those questions were nearly impossible to answer.

Data-driven decision making lies at the heart of departments across organizations. But to facilitate these decisions, analytics can no longer remain the purview of a small number of people who mete out reports as time allows — decision makers need direct access to analytics.

Data science is a big investment — hiring a data scientist could easily set you back six figures annually. But promises of increased profits have companies clamoring for deep analytics talent, regardless of cost.

Last year when we looked Gartner’s Magic Quadrant (MQ) for Business Intelligence and Analytics it held 24 vendors, which by any measure is a crowd.
Though the number hasn’t slimmed since then, new vendors have been added and others are no longer included.